Share Email Print
cover

Proceedings Paper

Practical automatic Arabic license plate recognition system
Author(s): Khader Mohammad; Sos Agaian; Hani Saleh
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Since 1970's, the need of an automatic license plate recognition system, sometimes referred as Automatic License Plate Recognition system, has been increasing. A license plate recognition system is an automatic system that is able to recognize a license plate number, extracted from image sensors. In specific, Automatic License Plate Recognition systems are being used in conjunction with various transportation systems in application areas such as law enforcement (e.g. speed limit enforcement) and commercial usages such as parking enforcement and automatic toll payment private and public entrances, border control, theft and vandalism control. Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. [License plate detection using cluster run length smoothing algorithm ].Generally, an automatic license plate localization and recognition system is made up of three modules; license plate localization, character segmentation and optical character recognition modules. This paper presents an Arabic license plate recognition system that is insensitive to character size, font, shape and orientation with extremely high accuracy rate. The proposed system is based on a combination of enhancement, license plate localization, morphological processing, and feature vector extraction using the Haar transform. The performance of the system is fast due to classification of alphabet and numerals based on the license plate organization. Experimental results for license plates of two different Arab countries show an average of 99 % successful license plate localization and recognition in a total of more than 20 different images captured from a complex outdoor environment. The results run times takes less time compared to conventional and many states of art methods.

Paper Details

Date Published: 17 February 2011
PDF: 12 pages
Proc. SPIE 7881, Multimedia on Mobile Devices 2011; and Multimedia Content Access: Algorithms and Systems V, 78810V (17 February 2011); doi: 10.1117/12.871769
Show Author Affiliations
Khader Mohammad, The Univ. of Texas at San Antonio (United States)
Sos Agaian, The Univ. of Texas at San Antonio (United States)
Hani Saleh, The Univ. of Texas at San Antonio (United States)


Published in SPIE Proceedings Vol. 7881:
Multimedia on Mobile Devices 2011; and Multimedia Content Access: Algorithms and Systems V
David Akopian; Cees G. M. Snoek; Nicu Sebe; Reiner Creutzburg; Lyndon Kennedy, Editor(s)

© SPIE. Terms of Use
Back to Top